Digital rendering devices such as printers typically rely on raster image processing for generating digital images (e.g., contone byte map) based on a compact input representation such as, for example, a PDL (Page Description Language) file. A DFE (Digital Front End) then processes an incoming rendering job in the form of the PDL file to create a print-ready rasterized image. The rasterized image may be then fed to a print engine for image rendering via paper or other printable media. The majority of processing cycles associated with the DFE may be consumed during the RIP operations. The processing time to rasterize the data and transfer the data to the print engine may slow the ability of the print engine to render data at a full-rated speed.
A prior art technique for improving RIP performance of a rendering job employs cached reusable objects to create a print-ready image (e.g., a compressed image). Such a print-ready image may include any number of independent JPEG tiles, which are generally expanded and assembled at the time of rendering. The JPEG tiles may overlap one another, resulting in the print-time expansion of data, which may subsequently be discarded. Consequently, an unbounded number of assembly operations are deferred from RIP-time until print-time. Such an approach, however, can result in a broken and/or a blank page as the print-time expansion and assembly operations are not completed based on an IOT (Image Output Terminal) speed. Additionally, the rendering system may not be able to operate in “real-time” and hence it is difficult to process and render extremely large amounts of data via such an approach.
Based on the foregoing, it is believed that a need exists for an improved system and method for predicting expansion difficulty and the expansion time required to perform print-time imaging operations. A need also exists for formulating a linear equation based on measured compression statistics for use in rendering operations, as described in greater detail herein.